Kandasamy Yogavijayan, Baker Stephanie
School of Medicine and Public Health, The University of Newcastle, Callaghan, NSW 2308, Australia.
Department of Neonatology, Townsville University Hospital, Townsville, QLD 4814, Australia.
Diagnostics (Basel). 2023 Sep 5;13(18):2865. doi: 10.3390/diagnostics13182865.
A preterm birth is a live birth that occurs before 37 completed weeks of pregnancy. Approximately 15 million babies are born preterm annually worldwide, indicating a global preterm birth rate of about 11%. Up to 50% of premature neonates in the gestational age (GA) group of <29 weeks' gestation will develop acute kidney injury (AKI) in the neonatal period; this is associated with high mortality and morbidity. There are currently no proven treatments for established AKI, and no effective predictive tool exists. We propose that the development of advanced artificial intelligence algorithms with neural networks can assist clinicians in accurately predicting AKI. Clinicians can use pathology investigations in combination with the non-invasive monitoring of renal tissue oxygenation (rSO) and renal fractional tissue oxygenation extraction (rFTOE) using near-infrared spectroscopy (NIRS) and the renal resistive index (RRI) to develop an effective prediction algorithm. This algorithm would potentially create a therapeutic window during which the treating clinicians can identify modifiable risk factors and implement the necessary steps to prevent the onset and reduce the duration of AKI.
早产是指在妊娠满37周之前的活产。全球每年约有1500万婴儿早产，全球早产率约为11%。在孕周小于29周的早产新生儿中，高达50%在新生儿期会发生急性肾损伤（AKI）；这与高死亡率和高发病率相关。目前对于已确诊的AKI尚无经证实的治疗方法，也不存在有效的预测工具。我们提出，开发具有神经网络的先进人工智能算法可协助临床医生准确预测AKI。临床医生可以结合病理检查，使用近红外光谱（NIRS）对肾组织氧合（rSO）和肾组织氧合分数提取（rFTOE）进行无创监测以及肾阻力指数（RRI），来开发一种有效的预测算法。该算法可能会创造一个治疗窗口，在此期间，治疗临床医生可以识别可改变的风险因素，并采取必要措施预防AKI的发生并缩短其持续时间。
